This research proposes a new hybrid path planning method to improve common global path planning,real-time tracking and obstacle avoidance problems in large-scale dynamic environments.Firstly,this paper designs a secure A* algorithm that simplifies the calculation of risk cost function and distance cost.Secondly,key path points are extracted from the planned path generated by safety A* algorithm,thereby reducing the number of grid nodes and achieving smooth path tracking.Finally,a real-time motion planning method based on adaptive windows is used to realize simultaneous path tracking and obstacle avoidance(SPTaOA)while switching critical path points.The feasibility and performance of the method are verified by simulation and practical experiments.The research results show that the proposed hybrid path planning method can meet the application requirements of mobile robots in large-scale dynamic environments,and realize an effective combination of global path planning,tracking and obstacle avoidance.
维普
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